Data-Driven Bayesian Network Analysis of Railway Accident Risk

Ensuring railway safety is a top priority, with a central focus on preventing accidents. By thoroughly analyzing data from railway accident investigations, we can pinpoint factors and patterns associated with different types of railway accidents. This proactive approach not only helps reduce the fre...

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Veröffentlicht in:	IEEE access 2024-01, Vol.12, p.1-1
Hauptverfasser:	Shi, Lei, Liu, Yazhi, Zhang, Youpeng, Liang, Junyi
Format:	Artikel
Sprache:	eng
Schlagworte:	Accident investigation Accident investigations Accident prevention Analytical models Bayes methods Bayesian analysis Bayesian networks Bridge failure Data analysis Data models data-driven Impact damage Level crossings Network analysis Predictive models Rail transportation Railroad accidents & safety Railway accidents Railway safety Risk analysis Risk factors Safety Sensitivity analysis System failures Transportation safety tree-augmented naive Bayes
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